基于粒子滤波的无线传感器网络目标跟踪

本文首先介绍了PF(Particle Filter)和UPF(Unscented Particle Filter)的基本原理,然后针对无线传感器网络(WSN)目标跟踪这一应用方向,采用等级网络结构,参考分布式粒子滤波算法,将UPF应用于WSN单目标跟踪以提高网络跟踪精度,仿真证明UPF较PF在跟踪精度上确实有明显的提高。     

Maximum correntropy criterion variational Bayesian adaptive Kalman filter based on strong tracking with unknown noise covariances

The performance of the current state estimation will degrade in the existence of slow-varying noise statistics. To solve the aforementioned issues, an improved strong tracking maximum correntropy criterion variational-Bayesian adaptive Kalman filter is presented in this paper. First of all, the inverse-Wishart distribution, as the conjugate-prior, is adopted to model the unknown and time-varying measurement and process noise covariances, then the noise covariances and system state are estimated via the variational Bayesian method. Secondly, the multiple fading-factors are obtained and evaluated to modify the prediction error covariance matrix to address the problems associated with inaccurate error estimation. Finally, the maximum correntropy criterion is employed to correct the filtering gain, which improves the filtering performance of the proposed algorithm. Simulation results show that the proposed filter exhibits better accuracy and convergence performance compared to other existing algorithms.     

Fault-tolerant tracking control based on reinforcement learning with application to a steer-by-wire system

In this paper, a novel complete model-free integral reinforcement learning (CMFIRL) algorithm based fault tolerant control scheme is proposed to solve the tracking problem of steer-by-wire (SBW) system. We begin with the recognition that the reference errors can eventually converge to zero based on the command generator model. Then an augmented tracking system is constructed with a corresponding performance index which is considered as a type of actuator failure. By using the reinforcement learning (RL) technique, three novel online update strategies are respectively developed to cope with the following three cases, i.e., model-based, partially model-free, and completely model-free. Especially, the RL algorithm for the complete model-free case eliminates the constraints of requiring the known system dynamics in fault-tolerant tracking controlling. The system stability and the convergence of the CMFIRL iteration algorithm are also rigorously proved. Finally, a simulation example is given to illustrate the effectiveness of the proposed approach.     

Asymptotic adaptive tracking control and application to mechatronic systems

This article develops an asymptotic tracking control strategy for uncertain nonlinear systems subject to additive disturbances and parametric uncertainties. To fulfill this work, an adaptive-gain disturbance observer (AGDO) is first designed to estimate additive disturbances and compensate them in a feedforward way, which eliminates the impact of additive disturbances on tracking performance. Meanwhile, an updated observer gain law driven by observer estimation errors is adopted in AGDO, which reduces the conservatism of observer gain selection and is beneficial to practical implementation. Also, the parametric uncertainties existing in systems are addressed via an integrated parametric adaptive law, which further decreases the learning burden of AGDO. Based on the parametric adaption technique and the proposed AGDO approach, a composite controller is employed. The stability analysis uncovers the system asymptotic tracking performance can be attained even when facing time-variant additive disturbances and parametric uncertainties. In the end, comparative experimental results of an actual mechatronic system driven by a dc motor uncover the validity of the developed approach.     

Reachable set estimation for discrete-time bilinear systems with time-varying delays

The problem of reachable set estimation is studied for discrete-time bilinear system in this paper. Time-varying delays and bounded input disturbances are both considered in bilinear system. The aim is to find reachable set that converges from all the states of system with initial conditions. By constructing Lyapunov–Krasovskii functional, sufficient delay-dependent less conservative stable conditions of reachable set estimation are obtained for bilinear delay system via the reciprocally convex combination and delay partition approaches. The derived theorem can guarantee that all the states of system with initial conditions from some domain are bounded in an ellipsoid and all the states from other domain are converged exponentially within a ball. One simulation example is presented to illustrate the correctness of the derived result in this paper.     

无源滤波器设计与评价软件的开发应用

电网谐波不仅降低了电能质量,还可能引起故障甚至事故。在工程实践中,通常在谐波数据超标的监测点安装无源滤波器。在实际安装之前,无源滤波器参数的设计是个关键。根据监测点实测的谐波数据,以及装置接入点供电系统参数等,本文给出无源滤波器参数设计方案,并进行滤波效果的评价,为供电部门提供参考,为电网谐波问题分析与治理提供参考方案。     

Actuator fault diagnosis for a class of bilinear systems with uncertainty

In this paper, the actuator fault diagnosis problem for a class of bilinear systems with uncertainty is discussed. The system is transformed into two different subsystems. One is not affected by actuator fault, so an adaptive observer can be designed such that, under certain conditions, the observer error dynamics is stable. The other whose states can be measured is affected by the faults. The observation scheme is then used for model-based fault diagnosis. Finally, an example of a semiactive suspension system is used to illustrate the applicability of the proposed method.     

Finite and infinite dimensional bilinear realizations

In this paper we discuss the realization of Volterra series by finite and infinite dimensional bilinear systems. We observe that realizing a given Volterra series with various weights leads naturally to a particularly interesting class of bilinear systems with a rich mathematical structure. We are able to use certain results on the shift realization of linear systems to arrive at a suitable analog of shift realizations for bilinear realizations.     

On controllability of discrete-time bilinear systems

In this paper, necessary and sufficient conditions for the controllability of a class of discrete-time bilinear systems are proposed, which extend the existing results and show that the controllability counterexample in [1] that is derived by Euler discretization of an uncontrollable bilinear system, is a special case of the necessary and sufficient conditions.     

基于共现分析的科技监测地图绘制及实证研究

科技监测作为一种有效的科技管理工具,可以为科技管理工作提供有力的决策信息支持。基于此,文章采用共现分析的方法,构建了一个三阶段的科技监测模型,并以可视化的形式将科技监测的结果进行图谱展示。在此基础上,以公路工程领域为例,进行科技监测的可视化实验,以此判别科技领域的深层次结构,为科技监测在科技管理中的应用提供一种思路和手段。     

Controllability of discrete-time inhomogeneous bilinear systems with real spectrum: Algebraically verifiable criteria

One of the drawbacks of the controllability theory for nonlinear systems is that most existing controllability criteria are not algebraically verifiable, which makes them difficult to apply especially if the system dimension is high. Thus, it is a significant task to seek algebraically verifiable controllability criteria for nonlinear systems. In this paper, we study controllability of discrete-time inhomogeneous bilinear systems. In the classical results on controllability of such systems, a necessary condition is that the linear part has to be controllable. However, we will show that this condition is in fact not necessary for controllability. Specifically, we first define the spectrum for discrete-time inhomogeneous bilinear systems and reveal that the spectrum is a fundamental property which is very useful in investigating the controllability problems. We then present controllability criteria for the systems with real spectrum, which are algebraically verifiable. Furthermore, we also provide algorithms for the controllable systems to compute the exact or approximated control inputs to achieve the transition between any given pair of states. The presented controllability criteria and algorithms work for the systems in any finite dimension and are easy to implement. More importantly, through our controllability criteria, we reveal that controllability of the linear part is not necessary for discrete-time inhomogeneous bilinear systems to be controllable. Examples are given to illustrate the presented algebraic controllability criteria.     

Minimal realizations and canonical forms for bilinear systems

The minimal realization theory for input–output maps that arise from finite- dimensional, continuous time, bilinear systems is discussed. It is shown that an observed bilinear system (i.e. a bilinear system together with an observation functional, but without a fixed initial state) is completely determined by its input–output correspondence, i.e. its multivalued input–output map. A precise formulation and proof of the result are given that continuous canonical forms for bilinear systems do not exist. This is done by adapting to the bilinear case an idea due to Hazewinkel and Kalman for the case of linear systems. In addition, the proof presented here has the advantage of not involving any algebraic geometry, which makes it considerably simpler than the original proof of the linear systems result.     

Combined state and parameter estimation for a bilinear state space system with moving average noise

This paper considers the identification problem of bilinear systems with measurement noise in the form of the moving average model. In particular, we present an interactive estimation algorithm for unmeasurable states and parameters based on the hierarchical identification principle. For unknown states, we formulate a novel bilinear state observer from input-output measurements using the Kalman filter. Then a bilinear state observer based multi-innovation extended stochastic gradient (BSO-MI-ESG) algorithm is proposed to estimate the unknown system parameters. A linear filter is utilized to improve the parameter estimation accuracy and a filtering based BSO-MI-ESG algorithm is presented using the data filtering technique. In the numerical example, we illustrate the effectiveness of the proposed identification methods.     

Design of adaptive sliding mode tracking controllers for chaotic synchronization and application to secure communications

Synchronization of two identical chaotic systems with matched and mismatched perturbations by utilizing adaptive sliding mode control (ASMC) technique is presented in this paper. The sliding surface function is specially designed based on the Lyapunov stability theorem and linear matrix inequality (LMI) optimization technique. The designed tracking controller can not only suppress the mismatched perturbations when the controlled dynamics (master–slave) are in the sliding mode, but also drive the trajectories of synchronization errors into a small bounded region whose size can be adjusted through the designed parameters. Adaptive mechanisms are employed in the proposed control scheme for adapting the unknown upper bounds of the perturbations, and the stability of overall controlled synchronization systems is guaranteed. The comparison of the proposed chaotic synchronization technique with an existing generalized chaotic synchronization (GCS) method as well as application of the proposed control method to secure communications is also demonstrated in this paper.     

Model reduction of bilinear systems based on Laguerre series expansion

We present a model reduction method for bilinear systems based on the Laguerre series expansion of the kernels resulting from the Volterra representation theory. By employing a two-sided projection, the reduced order system preserves a desired number of Laguerre coefficients, thereby approximating the original system faithfully. Furthermore, the relationship between the proposed Laguerre-based methods and the moment matching methods is studied, which reveals that these two approaches are equivalent under some specific conditions.     

Analysis and parameter estimation of bilinear systems via Chebyshev polynomials

The operational properties of the integration and product of Chebyshev polynomials are used in the analysis of bilinear systems by the approximation of time functions by truncated Chebyshev series. The operational properties are also applied to determine the unknown parameters of a general bilinear system from the input-output data. Examples with excellent results are given.     

Average-consensus tracking of multi-agent systems with additional interconnecting agents

Average-consensus tracking problem is investigated for first-order multi-agent systems composed of valid agents and additional interconnecting agents. Valid agents have constant reference inputs, while additional interconnecting agents do not have reference inputs. Average-consensus tracking algorithms are proposed for the agents converging to the average value of constant reference inputs of valid agents. Under symmetric and connected topology, consensus conditions are obtained for the agents without and with communication delay, respectively, by using generalized Nyquist criterion. Numerical examples illustrate the correctness of theoretical results.     

Optimal tracking performance for networked control systems with quantization

This paper investigates the optimal tracking performance of the multiple-input multiple-output (MIMO) discrete-time networked control systems (NCSs) considering the quantization of communication channel. The tracking performance is adopted for the H₂ square error criterion. The optimal tracking performance expression is obtained by using the co-prime factorization, the partial factorization, the inner–outer factorization and the spectral decomposition methods. Moreover, the paper also includes the exploration of the optimal tracking performance with input power constraint. The obtained results have demonstrated that the optimal tracking performance is influenced by the non-minimum phase zeros, unstable poles and their directions, the reference signal and the quantization interval. Moreover the theoretical results have also been proven using a number of different examples.     

Sliding mode attitude tracking of rigid spacecraft with disturbances

The attitude tracking control problem of a spacecraft nonlinear model with external disturbances and inertia uncertainties is addressed in this paper. First, a new sliding mode controller is designed to ensure the asymptotic convergence of the attitude and angular velocity tracking errors against external disturbances and inertia uncertainties by using a modified differentiator to estimate the total disturbances. Second, an adaptive algorithm is applied to compensating the disturbances, by which another sliding mode controller is successfully designed to achieve a high performance on the attitude tracking in the presence of the inertia uncertainties, external disturbances and actuator saturations. Finally, simulation results are presented to illustrate effectiveness of the control strategies.